Forecasting Volatilities of Corn Futures at Distant Horizons

Accurately forecasting volatility at distant horizons is critical for managing long-term risk in agriculture. Given the poor performance of GARCH-type models at long-term volatility forecast, we develop a risk-adjusted implied volatility, which adjust the risk-neutral implied volatility by correctly accounting for the volatility risk premium. The paper evaluates the performance of the new implied volatility in the corn futures market relative to two alternative forecasts- a three-year moving average forecast and a naïve forecast. The finding from the study is that the new implied volatilities have at least as well as or stronger predictive power than alternative predicting approaches.


Issue Date:
2010
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/61316
Total Pages:
20
Series Statement:
Selected Paper
10942




 Record created 2017-04-01, last modified 2017-08-25

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